Partnership Process Guidelines: Social Work Perspectives on Creating and Sustaining Real-World University-Community Partnerships

The authors, representing community practitioners, faculty, students, and administration, collaborated to produce guidelines for university-community partnerships that reflect social work’s commitment to social justice in practice, education, and research. The respective experiences and voices of the authors contribute to a wider perspective on the explicit social justice implications of partnership formation for community-based participatory research, which is a vision shared by many disciplines. These guidelines introduce a communication outline that may augment the creation and maintenance of thriving university-community partnerships across multiple disciplines that promote social justice

Cadmium-Induced Oxidative Stress and Apoptotic Changes in the Testis of Freshwater Crab, Sinopotamon henanense

Cadmium (Cd), one of the most toxic environmental and industrial pollutants, is known to exert gonadotoxic and spermiotoxic effects. In the present study, we examined the toxic effect of Cd on the testis of freshwater crab, Sinopotamon henanense. Crabs were exposed to different Cd concentrations (from 0 to 116.00 mg·L−1) for 7 d. Oxidative stress and apoptotic changes in the testes were detected. The activities of SOD, GPx and CAT initially increased and subsequently decreased with increasing Cd concentrations, which was accompanied with the increase in malondialdehyde (MDA) and H2O2 content in a concentration-dependent manner. Typical morphological characteristic and physiological changes of apoptosis were observed using a variety of methods (HE staining, AO/EB double fluorescent staining, Transmission Electron Microscope observation and DNA fragmentation analysis), and the activities of caspase-3 and caspase-9 were increased in a concentration-dependent manner after Cd exposure. These results led to the conclusion that Cd could induced oxidative damage as well as apoptosis in the testis, and the apoptotic processes may be mediated via mitochondria-dependent apoptosis pathway by regulating the activities of caspase-3 and caspase-9

Speeding up a genetic algorithm for EPR-based spin label characterization of biosystem complexity

Complexity of biological systems is one of the toughest problems for any experimental technique. Complex biochemical composition and a variety of biophysical interactions governing the evolution of a state of a biological system imply that the experimental response of the system would be superimposed of many different responses. To obtain a reliable characterization of such a system based on spin-label Electron Paramagnetic Resonance (EPR) spectroscopy, multiple Hybrid Evolutionary Optimization (HEO) combined with spectral simulation can be applied. Implemented as the GHOST algorithm this approach is capable of handling the huge solution space and provides an insight into the "quasicontinuous© distribution of parameters that describe the biophysical properties of an experimental system. However, the analysis procedure requires several hundreds of runs of the evolutionary optimization routine making this algorithm extremely computationally demanding. As only the best parameter sets from each run are assumed to contribute into the final solution, this algorithm appears far from being optimized. The goal of this study is to modify the optimization routine in a way that 20-40 runs would be enough to obtain qualitatively the same characterization. However, to keep the solution diversity throughout the HEO run, fitness sharing and newly developed shaking mechanisms are applied and tested on various test EPR spectra. In addition, other evolutionary optimization parameters such as population size and probability of genetic operators were also varied to tune the algorithm. According to the testing examples a speed-up factor of 5-7 was achieved

Spin label EPR-based characterization of biosystem complexity

Following the widely spread EPR spin-label applications for biosystem characterization, a novel approach is proposed for EPR-based characterization of biosystem complexity. Hereto a computational method based on a hybrid evolutionary optimization (HEO) is introduced. The enormous volume of information obtained from multiple HEO runs is reduced with a novel so-called GHOST condensation method for automatic detection of the degree of system complexity through the construction of two-dimensional solution distributions. The GHOST method shows the ability of automatic quantitative characterization of groups of solutions, e.g. the determination of average spectral parameters and group contributions. The application of the GHOST condensation algorithm is demonstrated on four synthetic examples of different complexity and applied to two physiologically relevant examples- the determination of domains in biomembranes (lateral heterogeneity) and the study of the low-resolution structure of membrane proteins